Python urllib2.urlopen() is slow, need a better way to read several urls

Question

As the title suggests, I'm working on a site written in python and it makes several calls to the urllib2 module to read websites. I then parse them with BeautifulSoup.

As I have to read 5-10 sites, the page takes a while to load.

I'm just wondering if there's a way to read the sites all at once? Or anytricks to make it faster, like should I close the urllib2.urlopen after each read, or keep it open?

Added: also, if I were to just switch over to php, would that be faster for fetching and Parsi g HTML and XML files from other sites? I just want it to load faster, as opposed to the ~20 seconds it currently takes

Answer 1

I'm rewriting Dumb Guy's code below using modern Python modules like threading and Queue.

import threading, urllib2
import Queue

urls_to_load = [
'http://stackoverflow.com/',
'http://slashdot.org/',
'http://www.archive.org/',
'http://www.yahoo.co.jp/',
]

def read_url(url, queue):
    data = urllib2.urlopen(url).read()
    print('Fetched %s from %s' % (len(data), url))
    queue.put(data)

def fetch_parallel():
    result = Queue.Queue()
    threads = [threading.Thread(target=read_url, args = (url,result)) for url in urls_to_load]
    for t in threads:
        t.start()
    for t in threads:
        t.join()
    return result

def fetch_sequencial():
    result = Queue.Queue()
    for url in urls_to_load:
        read_url(url,result)
    return result

Best time for find_sequencial() is 2s. Best time for fetch_parallel() is 0.9s.

Also it is incorrect to say thread is useless in Python because of GIL. This is one of those case when thread is useful in Python because the the threads are blocked on I/O. As you can see in my result the parallel case is 2 times faster.